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Alex Lyman; Bryce Hepner; Lisa P. Argyle; Ethan C. Busby; Joshua R. Gubler; David Wingate – Sociological Methods & Research, 2025
Generative artificial intelligence (AI) has the potential to revolutionize social science research. However, researchers face the difficult challenge of choosing a specific AI model, often without social science-specific guidance. To demonstrate the importance of this choice, we present an evaluation of the effect of alignment, or human-driven…
Descriptors: Artificial Intelligence, Computer Simulation, Open Source Technology, Social Science Research
Bulut, Okan; Yildirim-Erbasli, Seyma Nur – International Journal of Assessment Tools in Education, 2022
Reading comprehension is one of the essential skills for students as they make a transition from learning to read to reading to learn. Over the last decade, the increased use of digital learning materials for promoting literacy skills (e.g., oral fluency and reading comprehension) in K-12 classrooms has been a boon for teachers. However, instant…
Descriptors: Reading Comprehension, Natural Language Processing, Artificial Intelligence, Automation
Dragos-Georgian Corlatescu; Micah Watanabe; Stefan Ruseti; Mihai Dascalu; Danielle S. McNamara – Grantee Submission, 2024
Modeling reading comprehension processes is a critical task for Learning Analytics, as accurate models of the reading process can be used to match students to texts, identify appropriate interventions, and predict learning outcomes. This paper introduces an improved version of the Automated Model of Comprehension, namely version 4.0. AMoC has its…
Descriptors: Computer Software, Artificial Intelligence, Learning Analytics, Natural Language Processing
Conrad Borchers; Tianze Shou – Grantee Submission, 2025
Large Language Models (LLMs) hold promise as dynamic instructional aids. Yet, it remains unclear whether LLMs can replicate the adaptivity of intelligent tutoring systems (ITS)--where student knowledge and pedagogical strategies are explicitly modeled. We propose a prompt variation framework to assess LLM-generated instructional moves' adaptivity…
Descriptors: Benchmarking, Computational Linguistics, Artificial Intelligence, Computer Software
Bogdan Nicula; Mihai Dascalu; Tracy Arner; Renu Balyan; Danielle S. McNamara – Grantee Submission, 2023
Text comprehension is an essential skill in today's information-rich world, and self-explanation practice helps students improve their understanding of complex texts. This study was centered on leveraging open-source Large Language Models (LLMs), specifically FLAN-T5, to automatically assess the comprehension strategies employed by readers while…
Descriptors: Reading Comprehension, Language Processing, Models, STEM Education
Connor David Nelson – ProQuest LLC, 2024
This dissertation introduces a comprehensive framework aimed at reshaping applied cybersecurity education to significantly ease the learning curve, at scale, through three synergistic innovations. These methods address the daunting educational barriers in cybersecurity, enabling learners at all levels to understand complex security concepts more…
Descriptors: Computer Security, Information Security, Computer Science Education, Models
International Association for Development of the Information Society, 2012
The IADIS CELDA 2012 Conference intention was to address the main issues concerned with evolving learning processes and supporting pedagogies and applications in the digital age. There had been advances in both cognitive psychology and computing that have affected the educational arena. The convergence of these two disciplines is increasing at a…
Descriptors: Academic Achievement, Academic Persistence, Academic Support Services, Access to Computers

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